Organochlorine compounds such as DDT and PCB are detectable in the blood of most Americans. These compounds have been designated as possibly or probably carcinogenic by the International Agency for Research on Cancer. Some recent reports suggest that risk of breast cancer is proportional to exposure to DDE, a degradation product of DDT, and to PCB. These reports were each based on fewer than 60 cases. Results from another, larger study suggest no associations exist; additional data are needed. African- Americans have had greater exposure to DDE than white Americans, thus an examination of the DDE-breast cancer association in African-Americans may have greater statistical power to detect an effect than studies in lesser- exposed populations. We propose to conduct a case-control study to test the hypothesis that levels of organochlorine residues in serum are associated with increased risk of breast cancer among African-American women. The study will be added on to ongoing study funded by the National Institute of Child Health and Development. The ongoing study, the Women's Contraceptive and Reproductive Experience (CARE) study, is a multi-center population-based case-control study being conducted among women aged 35-64 in five areas of the U.S., including Los Angeles County. For the present study, we will enroll a subset of the African-American participants in Los Angeles County. Cases will be identified through the Los Angeles County Cancer Surveillance Program (a SEER cancer registry).. Controls will be selected by random-digit dialing. After subjects have completed interviews for the Women's CARE study, they will be asked to provide a blood specimen for the present study. We will obtain blood from 300 African-American breast cancer cases and 300 controls and measure serum organochlorine residues (DDE, PCBs, heptachlor epoxide, oxychlordane, trans-nonachlor, dieldrin, HCB, and beta-BHC) and total lipids using standard methods. Serum residue levels will be examined in relation to odds of breast cancer in multivariate unconditional logistic regression models.